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Bayesian methods for large scale small area estimation (SAE)

Summary of the impact

Small area estimation (SAE) describes the use of Bayesian modelling of survey and administrative data in order to provide estimates of survey responses at a much finer level than is possible from the survey alone. Over the recent past, academic publications have mostly targeted the development of the methodology for SAE using small-scale examples. Only predictions on the basis of realistically sized samples have the potential to impact on governance and our contribution is to fill a niche by delivering such SAEs on a national scale through the use of a scaling method. The impact case study concerns the use of these small area predictions to develop disease-level predictions for some 8,000 GPs in England and so to produce a funding formula for use in primary care that has informed the allocation of billions of pounds of NHS money. The value of the model has been recognised in NHS guidelines. The methodology has begun to have impact in other areas, including the BIS `Skills for Life' survey.

Submitting Institution

Plymouth University

Unit of Assessment

Mathematical Sciences

Summary Impact Type

Societal

Research Subject Area(s)

Mathematical Sciences: Statistics
Economics: Econometrics

Improved Insurance Products for the Multinational Insurance Industry

Summary of the impact

Our research has been applied directly by Aviva plc. to develop improved products in the general insurance market (e.g. household and car) and in the more specialised area of enhanced pension annuities. As a result, Aviva has become more competitive in these markets and customers are enjoying better value for money. In the case of enhanced annuities, the benefits are in the form of higher pension income for those accurately identified as facing shortened life expectancies. Aviva is the largest insurance company in the UK and the sixth largest in the world.

Submitting Institution

University of East Anglia

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Economic

Research Subject Area(s)

Mathematical Sciences: Statistics
Economics: Applied Economics, Econometrics

Impact on the Statistical Confidentiality Practices of Data Stewardship Organisations

Summary of the impact

Research at the University of Manchester (UoM) has developed new approaches, methods and algorithms to improve the statistical confidentiality practices of data stewardship organisations (DSOs), such as the UK's Office for National Statistics. The research and its products have had significant impacts on data dissemination practice, both in the UK and internationally, and have been adopted by national statistical agencies, government departments and private companies. The primary beneficiaries of this work are DSOs, who are able to both disseminate useful data products, and protect respondent confidentiality more effectively. Secondary beneficiaries are respondents, whose confidentiality is better protected, and the research community, as without `gold standard' disclosure risk analysis, data holders can be overcautious.

Submitting Institution

University of Manchester

Unit of Assessment

Sociology

Summary Impact Type

Societal

Research Subject Area(s)

Mathematical Sciences: Statistics
Economics: Applied Economics

Establishing a blueprint for administrative data based longitudinal studies in the UK

Summary of the impact

The Scottish Longitudinal Study (SLS) is a pioneering study, combining census, civil registration, health and education data (administrative data). It has established an approach that allows the legal and ethical use of personal, sensitive information by maintaining anonymity within the data system. This approach has become a model for the national data linkage systems that are now being established across the UK. The SLS has also enabled policy analysts to monitor key characteristics of the Scottish population in particular health inequalities (alerting policy makers to Scotland's poor position within Europe), migration (aiding economic planning) and changing tenure patterns (informing house building decisions). Finally, the study has become fully embedded in Scotland's National Statistical agency, allowing it to produce new informative statistical series.

Submitting Institution

University of St Andrews

Unit of Assessment

Geography, Environmental Studies and Archaeology

Summary Impact Type

Political

Research Subject Area(s)

Mathematical Sciences: Statistics
Medical and Health Sciences: Public Health and Health Services
Economics: Applied Economics

Intelligent Systems incorporating Automatic Classification and Carbon Footprinting for Corporate E-Procurement

Summary of the impact

Two Knowledge Transfer Partnership projects, carried out between 2006 and 2009, between an e-commerce marketplace provider (@UK plc) and the University of Reading, led to the development of two software tools that were launched in 2010. The tools, SpendInsight and GreenInsight, are the first of their kind to use artificial intelligence techniques to handle the extremely challenging data associated with purchasing in large organisations. Since their launch, these tools have been used by @UK plc to identify procurement savings and environmental costs of procurement activities for governments, multi-national corporations, academic institutions and healthcare providers. Over the last three years @UK plc has benefitted from the launch of these products as it has provided them with a competitive advantage over the market place, increased the quality and efficiency of their spend analyses and led to multi-million pound licensing agreements. An analysis of spending in some of the NHS Trust Foundations has led to changes in procurement behaviours that have resulted in hundreds of thousands of pounds saved to date — benefitting not only the NHS, but also taxpayers.

Submitting Institution

University of Reading

Unit of Assessment

Electrical and Electronic Engineering, Metallurgy and Materials

Summary Impact Type

Economic

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing, Information Systems
Economics: Applied Economics

Improving Social Care Call Centre Operational Effectiveness

Summary of the impact

Targeted Projection Pursuit (TPP) — developed at Northumbria University — is a novel method for interactive exploration of high-dimension data sets without loss of information. The TPP method performs better than current dimension-reduction methods since it finds projections that best approximate a target view enhanced by certain prior knowledge about the data. "Valley Care" provides a Telecare service to over 5,000 customers as part of Northumbria Healthcare NHS Foundation Trust, and delivers a core service for vulnerable and elderly people (receiving an estimated 129,000 calls per annum) that allows them to live independently and remain in their homes longer. The service informs a wider UK ageing community as part of the NHS Foundation Trust.

Applying our research enabled the managers of Valley Care to establish the volume, type and frequency of calls, identify users at high risk, and to inform the manufacturers of the equipment how to update the database software. This enabled Valley Care managers and staff to analyse the information quickly in order to plan efficiently the work of call operators and social care workers. Our study also provided knowledge about usage patterns of the technology and valuably identified clients at high risk of falls. This is the first time that mathematical and statistical analysis of data sets of this type has been done in the UK and Europe.

As a result of applying the TPP method to its Call Centre multivariate data, Valley Care has been able to transform the quality and efficiency of its service, while operating within the same budget.

Submitting Institution

Northumbria University Newcastle

Unit of Assessment

Mathematical Sciences

Summary Impact Type

Technological

Research Subject Area(s)

Mathematical Sciences: Statistics
Information and Computing Sciences: Artificial Intelligence and Image Processing, Information Systems

Estimating local populations with far greater accuracy using administrative data

Summary of the impact

There is growing evidence that official population statistics based on the decennial UK Census are inaccurate at the local authority level, the fundamental administrative unit of the UK. The use of locally-available administrative data sets for counting populations can result in more timely and geographically more flexible data which are more cost-effective to produce than the survey-based Census. Professor Mayhew of City University London has spent the last 13 years conducting research on administrative data and their application to counting populations at local level. This work has focused particularly on linking population estimates to specific applications in health and social care, education and crime. Professor Mayhew developed a methodology that is now used as an alternative to the decennial UK Census by a large number of local councils and health care providers. They have thereby gained access to more accurate, detailed and relevant data which have helped local government officials and communities make better policy decisions and save money. The success of this work has helped to shape thinking on statistics in England, Scotland and Northern Ireland and has contributed to the debate over whether the decennial UK Census should be discontinued.

Submitting Institution

City University, London

Unit of Assessment

Business and Management Studies

Summary Impact Type

Political

Research Subject Area(s)

Medical and Health Sciences: Public Health and Health Services
Economics: Applied Economics

Leading the open data revolution

Summary of the impact

Open Data has lowered barriers to data access, increased government transparency and delivered significant economic, social and environmental benefits. Southampton research and leadership has led to the UK Public Data Principles, which were enshrined in the UK Government Open Data White Paper, and has led to data.gov.uk, which provides access to 10,000 government datasets. The open datasets are proving means for strong citizen engagement and are delivering economic benefit through the £10 million Open Data Institute. These in turn have placed the UK at the forefront of the global data revolution: the UK experience has informed open data initiatives in the USA, EU and G8.

Submitting Institution

University of Southampton

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Political

Research Subject Area(s)

Mathematical Sciences: Statistics
Information and Computing Sciences: Information Systems

A new product for creating annotated data sets within smart environments

Summary of the impact

[text removed for publication], a developer of high-precision medical devices, have produced a new data annotation tool ([text removed for publication]) based on research in CSRI on data storage formats and activity recognition for applications within smart home environments. Within [text removed for publication] stereo-based cameras record activities in a specified environment (e.g. kitchen) which are then annotated using user-based pre-configured activity labels (e.g. prepare meal, wash dishes). [text removed for publication] is currently used by [text removed for publication] users and has yielded additional sales worth [text removed for publication]. [text removed for publication] have employed [text removed for publication] additional technical development staff to extend [text removed for publication] functionality, and through an MoU [text removed for publication] now supports automated annotation based on CSRI's research on activity recognition.

Submitting Institution

University of Ulster

Unit of Assessment

Computer Science and Informatics

Summary Impact Type

Technological

Research Subject Area(s)

Information and Computing Sciences: Artificial Intelligence and Image Processing, Information Systems

Freshwater Information Management and Data Sharing to Meet Environmental Standards

Summary of the impact

The advanced information management research of the Department of Digital Humanities (DDH) has led to a better understanding of pollution processes in inland waterways and lakes. It has also improved the standard of water quality information that is available to government and regulatory authorities. The information management framework which DDH has provided supports government-funded activities to improve environmental standards and has helped ensure that the UK Environment Agency is able to comply with the EU's Water Framework Directive, reducing the risk of financial penalties for non-compliance. Moreover, key and accurate evidence about water quality has been made freely available to beneficiaries, including governmental and non-governmental agencies, farmers and land managers, and the general public.

Submitting Institution

King's College London

Unit of Assessment

Communication, Cultural and Media Studies, Library and Information Management 

Summary Impact Type

Environmental

Research Subject Area(s)

Information and Computing Sciences: Information Systems
Economics: Applied Economics

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